code: def test_softmax_derivative(backend_default):
      inputs = np.array([0, 1, -2]).reshape((3, 1))
      outputs = np.ones((1, 1))  # shortcut only
      compare_tensors(Softmax(), inputs, outputs, deriv=True)
  
imports: from math import tanh
  import numpy
  from neon import NervanaObject
  from neon.transforms import Identity, Rectlin, Softmax, Tanh, Logistic, Sign, PixelwiseSoftmax
  from utils import allclose_with_out
label_desc: Use image node_id 17 for calling a global function with example usage: test_softmax_derivative(backend_default) without return types